No description available.

No description available.

No description available.

The use of chemiluminescence measurements to monitor a range of combustion processes has been a popular area of study due to their reliable and cost-effective nature. Electronically excited carbon dioxide (CO2*) is known for its broadband emission, and its detection can lead to valuable information; however, due to its broadband characteristics, CO2* is difficult to isolate experimentally, and the chemical kinetics of this species is not well known. Although numerous works have monitored CO2* chemiluminescence, a full kinetic scheme for the species has yet to be developed. A series of shock-tube experiments was performed in H2-N2O-CO mixtures highly diluted in argon at conditions where emission from CO2* could be isolated and monitored. These results were used to evaluate the kinetics of CO2*, in particular, the main CO2* formation reaction, CO + O + M CO2* + M (R1). Based on collision theory, the quenching chemistry of CO2* was determined for eleven common collision partners. The final mechanism developed for CO2* consisted of 14 reactions and 13 species. The rate for R1 was determined based on low-pressure experiments performed in two different H2-N2O-CO-Ar mixtures. Final mechanism predictions were compared with the experimental results at low and high pressures, with good agreement seen at both conditions. Peak CO2* trends with temperature as well as overall CO2* species time histories were both monitored. Comparisons were also made with previous experiments in methane-oxygen mixtures, where there was slight over-prediction of CO2* experimental trends by the mechanism.Experimental results and mechanism predictions were also compared with past literature rates for CO2*, with good agreement for peak CO2* trends, and slight discrepancies in overall CO2* species time histories. Overall, the ability of the CO2* mechanism developed in this work to reproduce a range of experimental trends represents an improvement over existing models.

A Bayesian framework for quantification of uncertainties has been used to quantify the uncertainty introduced by chemistry models. This framework adopts a probabilistic view to describe the state of knowledge of the chemistry model parameters and simulation results. Given experimental data, this method updates the model parameters' values and uncertainties and propagates that parametric uncertainty into simulations. This study focuses on syngas, a combination in various ratios of H2 and CO, which is the product of coal gasification. Coal gasification promises to reduce emissions by replacing the burning of coal with the less polluting burning of syngas. Despite the simplicity of syngas chemistry models, they nonetheless fail to accurately predict burning rates at high pressure. Three syngas models have been calibrated using laminar flame speed measurements. After calibration the resulting uncertainty in the parameters is propagated forward into the simulation of laminar flame speeds. The model evidence is then used to compare candidate models. Sensitivity studies, in addition to Bayesian methods, can be used to assess chemistry models. Sensitivity studies provide a measure of how responsive target quantities of interest (QoIs) are to changes in the parameters. The adjoint equations have been derived for laminar, incompressible, variable density reacting flow and applied to hydrogen flame simulations. From the adjoint solution, the sensitivity of the QoI to the chemistry model parameters has been calculated. The results indicate the most sensitive parameters for flame tip temperature and NOx emission. Such information can be used in the development of new experiments by pointing out which are the critical chemistry model parameters. Finally, a broader goal for chemistry model development is set through the adjoint methodology. A new quantity, termed field sensitivity, is introduced to guide chemistry model development. Field sensitivity describes how information of perturbations in flowfields propagates to specified QoIs. The field sensitivity, mathematically shown as equivalent to finding the adjoint of the primal governing equations, is obtained for laminar hydrogen flame simulations using three different chemistry models. Results show that even when the primal solution is sufficiently close for the three mechanisms, the field sensitivity can vary. / text

Rapid consumption of energy storage and serious environmental pollution demand more advanced combustion strategies and more renewable fuels. Development of chemical kinetic models and suitable selection of fuels are key factors in evolving and optimizing new engine and combustion concepts. Alkenes are typical composition of gasoline as well as typical intermediates in the oxidation of larger alkanes and alcohol, while isoprene is one of the important alkenes impacting both the atmospheric pollution and energy depletion. Isoprene is one of the most important species in the atmosphere chemistry, dominating the carbon flux emitted by vegetation and accounting for forty percent of non-methane biogenic emissions globally. Isoprene has been recognized not only as a noteworthy precursor to polycyclic aromatic hydrocarbons but also as a promising fuel additive. Isoprene has been extensively investigated in the atmosphere chemistry, but its role as a critical diolefin in combustion chemistry has received less attention. Only A few researchers studied isoprene chemistry by carrying out pyrolysis experiments and theoretical calculations. To better understand the combustion chemistry of isoprene, this work presents a detailed experimental and kinetic modeling investigation. This study explored the chemical kinetics of isoprene oxidation in ignition delay times and speciation measurements. Our shock tube experiments for ignition delay times covered the temperatures of 680 – 1470 K, pressures of 1 – 30 bar, and equivalence ratios of 0.5 – 2. We measured laser-based time-resolved CO speciation in a low-pressure shock tube at temperatures of 900 – 1470 K, pressures of 1 and 4 bar, and equivalence ratios of 0.5 and 1. Major species concentrations were measured in a jet-stirred reactor at 680 – 1280 K, 1 bar, and φ = 0.5 – 2. Afterwards, we used 1,3-butadiene as a basis to develop fuel-specific isoprene sub-mechanism and coupled it with a C0-C5 core sub-mechanism. Finally we developed a comprehensive kinetic model including 1585 species and 6884 reactions and achieved a good agreement between the model’s predictions and the experiments. To our knowledge, this study is the first comprehensive effort to describe the process and provides valuable insights into isoprene oxidation. The work reported in the thesis also facilitates the better understanding of combustion chemistry of diolefins.

No description available.

Pollutant control and efficiency improvement propel the need for clean combustion research on internal combustion engines. To design cleaner fuels for advanced combustion engines, gasoline combustion chemistry must be both understood and developed. A comprehensive examination of gasoline combustion chemistry in a jet stirred reactor is introduced in this dissertation. Real gasoline fuels have thousands of hydrocarbon components, which complicate numerical simulation. To mimic the behavior of real gasoline fuels, surrogates, composed of a few hydrocarbon components, are offered as a viable approach. In this dissertation, combustion chemistry of n-heptane, a key surrogate component, is investigated first, followed by an evaluation of a surrogate kinetic model. Finally, real gasoline fuels are assessed with the surrogate kinetic model. Mass spectrometry was employed to measure intermediates in n-heptane low temperature chemistry. Reaction pathways of the observed intermediates were proposed and clarified. n-Heptane low temperature oxidation reaction scheme was expanded by the proposed reactions. After surrogate proposal and formation, a surrogate kinetic model was examined. Low temperature and high temperature chemistry were observed and predicted. The octane number and composition effect on low temperature oxidation reactivity were revealed. High temperature combustion chemistry was found to be similar among the different surrogates, and the surrogate kinetic model reproduced surrogate behavior well in both low and high temperatures. Finally, the proposed surrogate model was examined using real gasoline fuels. Five real FACE (fuel for advanced combustion engines) gasolines were selected as target fuels to cover a wide range of octane number, sensitivity and hydrocarbon compositions. Low temperature oxidation chemistry was investigated for two intermediate octane number gasolines, FACE A and C. For a high octane number gasoline, FACE F, key pollutant production pathways were the focus of high temperature combustion chemistry. Two low octane number gasolines, FACE I and J, were compared with three other FACE gasolines to clarify gasoline combustion chemistry over a wide range. The gasoline surrogate chemical kinetic model proved to be a comprehensive, viable, accurate and powerful approach for numerical simulations. The proposed gasoline surrogate chemical kinetic model can aid in the numerical design of advanced combustion engines.

<p>Diss. (sammanfattning) Umeå : Umeå universitet, 1993, härtill 7 uppsatser.</p> / digitalisering@umu

L'impact environnemental du trafic aérien fait maintenant l'objet d'une réglementation qui tend à se sévériser. Dans ce contexte, les industriels misent sur l'amélioration des technologies afin de réduire la consommation de carburant et l'émission de polluants. Ces phénomènes dépendent en grande partie des chemins réactionnels sous-jacents, qui peuvent s'avérer très complexes. La Simulation aux Grandes Échelles (SGE) est un outil intéressant afin d'étudier ces phénomènes pour un coût de calcul qui reste raisonnable. Cependant, les processus chimiques, s'ils sont considérés sans simplification, font intervenir des centaines d'espèces aux temps caractéristiques très différents au sein de processus non-linéaires qui induisent une forte raideur dans le système d'équations, et un coût de calcul prohibitif. Permettant de s'absoudre de ces problèmes tout en conservant une bonne capacité de prédiction des polluants, les Chimies Analytiquement Réduites (CAR) font l'objet d'une attention grandissante au sein de la communauté. Les CAR permettent de conserver la physique du problème considéré, en conservant les espèces et voies réactionnelles les plus importantes. Grâce à l'évolution toujours croissante des moyens de calculs, les CAR sont appliqués dans des configurations de plus en plus complexes. Les travaux de thèse ont principalement portés sur deux sujets. Premièrement, une étude poussée des techniques et outils permettant une réduction efficace et systématique de chimies détaillées. L'outil de réduction multiétapes YARC est retenu et exhaustivement employé dans la dérivation et la validation d'une série de CAR préservant la description de la structure de flamme. Ensuite, une investigation de la faisabilité et des bénéfices qu'apportent l'utilisation de CAR en LES, comparé a des approches plus classiques, sur des cas tests de complexité croissante. La première configuration étudiée est une chambre de combustion partiellement pré-mélangée brûlant de l'éthylène, étudiée expérimentalement au DLR. Différentes modélisations de la chimie sont considérées, dont un CAR développé spécifiquement pour ce cas test, et les résultats démontrent qu'une prise en compte des interactions flamme-écoulement est cruciale pour une prédiction juste de la structure de la flamme et des niveaux de suies. La seconde configuration est un brûleur diphasique, avec une injection directe pauvre, brûlant du Jet-A2. Dans cette étude, une approche novatrice pour la prise en compte de la complexité du fuel réel (HyChem) est considérée, permettant la dérivation d’un CAR. Les résultats sont excellents et valident la méthodologie tout en fournissant une analyse précieuse des interactions flamme-spray et de la formation de polluants (NOx) dans des flammes à la structure complexe. / Recent implementation of emission control regulations has resulted in a considerable demand from industry to improve the efficiency while minimizing the consumption and pollutant emissions of the next generation of aero-engine combustors. Those phenomena are shown to strongly depend upon the underlying complex chemical pathways and their interaction with turbulence. Large Eddy Simulation (LES) is an attractive tool to address those issues with high accuracy at a reasonable computing cost. However, the computation of accurate combustion chemistry remains a challenge. Indeed, combustion proceeds through complex and highly non-linear processes that involve up to hundreds of different chemical compounds, which significantly increases the computational time and often induces stiffness in the resolved equations. As a mean to circumvent these drawbacks while retaining the necessary kinetics for the prediction of pollutants, Analytically Reduced Chemistry (ARC) has recently received high interest in the Computational Fluid Dynamics (CFD) community. ARC is a strategy for the description of combustion chemistry where only the most important species and reactions are retained, in a "physically-oriented way". ARC is on the verge of becoming affordable at a design stage, thanks to the continuously increasing available computational resources. The goal of the present work is twofold. A first objective is to test and validate efficient techniques and tools by which detailed chemistries are reduced to an LES-compliant format. To do so, the multi-step reduction tool YARC is selected and employed to derive and validate a series of ARC specifically designed to retrieve correct flame structures. A second objective is to investigate the overall feasibility and benefits of using ARC, combined to the Thickened Flame model (DTFLES), in performing LES of configurations of increasing complexity. The first configuration is a sooting swirl-stabilized non-premixed aero-engine combustor experimentally studied at DLR, burning ethylene. LES of this configuration is performed with the AVBP solver, in which ARC has been implemented. By comparison with global chemistry and tabulated chemistry, results highlight the importance of accurately capturing the flow-flame interactions for a good prediction of pollutants and soot. The second configuration is a swirled twophase flow burner featuring a lean direct injection system and burning Jet-A2. A novel methodology to real fuel modeling (HyChem approach) is employed, which allows subsequent ARC derivation. The excellent results in comparison with measurements constitute an additional validation of the methodology, and provide valuable qualitative and quantitative insights on the flame-spray interactions and on the pollutant formation (NOx) mechanisms in complex flame configurations.