Autoignition of non-premixed methane-air mixtures is investigated using first-order Conditional Moment closure (CMC). In CMC, scalar quantities are conditionally averaged with respect to a conserved scalar, usually the mixture fraction. The conditional fluctuations are often of small order, allowing the chemical source term to be modeled as a function of the conditional species concentrations and the conditional enthalpy (temperature). The first-order CMC derivation leaves many terms unclosed such as the conditional scalar dissipation rate, velocity and turbulent fluxes, and the probability density function. Submodels for these quantities are discussed and validated against Direct Numerical Simulations (DNS). The CMC and the turbulent velocity and mixing fields calculations are decoupled based on the frozen mixing assumption, and the CMC equations are cross-stream averaged across the flow following the shear flow approximation. Finite differences are used to discretize the equations, and a two-step fractional method is implemented to treat separately the stiff chemical source term. The stiff ODE solver LSODE is used to solve the resulting system of equations. The recently developed detailed chemical kinetics mechanism UBC-Mech 1.0 is employed throughout this study, and preexisting mechanisms are visited. Several ignition criteria are also investigated. Homogeneous and inhomogeneous CMC calculations are performed in order to investigate the role of physical transport in autoignition. Furthermore, the results of the perfectly homogeneous reactor calculations are presented and the critical value of the scalar dissipation rate for ignition is determined. The results are compared to the shock tube experimental data of Sullivan et al. The current results show good agreement with the experiments in terms of both ignition delay and ignition kernel location, and the trends obtained in the experiments are successfully reproduced. The results were shown to be sensitive to the scalar dissipation model, the chemical kinetics, and the ignition criterion.

Autoignition of non-premixed methane-air mixtures is investigated using first-order Conditional Moment closure (CMC). In CMC, scalar quantities are conditionally averaged with respect to a conserved scalar, usually the mixture fraction. The conditional fluctuations are often of small order, allowing the chemical source term to be modeled as a function of the conditional species concentrations and the conditional enthalpy (temperature). The first-order CMC derivation leaves many terms unclosed such as the conditional scalar dissipation rate, velocity and turbulent fluxes, and the probability density function. Submodels for these quantities are discussed and validated against Direct Numerical Simulations (DNS). The CMC and the turbulent velocity and mixing fields calculations are decoupled based on the frozen mixing assumption, and the CMC equations are cross-stream averaged across the flow following the shear flow approximation. Finite differences are used to discretize the equations, and a two-step fractional method is implemented to treat separately the stiff chemical source term. The stiff ODE solver LSODE is used to solve the resulting system of equations. The recently developed detailed chemical kinetics mechanism UBC-Mech 1.0 is employed throughout this study, and preexisting mechanisms are visited. Several ignition criteria are also investigated. Homogeneous and inhomogeneous CMC calculations are performed in order to investigate the role of physical transport in autoignition. Furthermore, the results of the perfectly homogeneous reactor calculations are presented and the critical value of the scalar dissipation rate for ignition is determined. The results are compared to the shock tube experimental data of Sullivan et al. The current results show good agreement with the experiments in terms of both ignition delay and ignition kernel location, and the trends obtained in the experiments are successfully reproduced. The results were shown to be sensitive to the scalar dissipation model, the chemical kinetics, and the ignition criterion.

<p>The current interest regarding how to stop the global warming has put focus on the automobile industry and forced them to produce vehicles/engines that are more environmental friendly. This has led to the development of increasingly complex controlsystem of the engines. The introduction of common-rail systems in regular automotives increased the demand of physical models that in an accurate way can describe the complex cycle within the combustion chamber. With these models implemented it is possible to test new strategies on engine steering in a cost- and time efficient way.</p><p>The main purpose with this report is to, build our own model based on the existing theoretical models in diesel engine combustion. The model has then been evaluated in a simulation environment using Matlab/Simulink. The model that has been implemented is a multi-zone type and is able to handle multiple injections.</p><p>The model that this thesis results in can in a good way predict both pressure and torque generated in the cylinder. More investigation in how the parameter settings behave in other work-points must be done to enhance the models accuracy. There is also some work left to do in the validation of the model but to make this possible more experimental data must be accessible.</p>

The current interest regarding how to stop the global warming has put focus on the automobile industry and forced them to produce vehicles/engines that are more environmental friendly. This has led to the development of increasingly complex controlsystem of the engines. The introduction of common-rail systems in regular automotives increased the demand of physical models that in an accurate way can describe the complex cycle within the combustion chamber. With these models implemented it is possible to test new strategies on engine steering in a cost- and time efficient way. The main purpose with this report is to, build our own model based on the existing theoretical models in diesel engine combustion. The model has then been evaluated in a simulation environment using Matlab/Simulink. The model that has been implemented is a multi-zone type and is able to handle multiple injections. The model that this thesis results in can in a good way predict both pressure and torque generated in the cylinder. More investigation in how the parameter settings behave in other work-points must be done to enhance the models accuracy. There is also some work left to do in the validation of the model but to make this possible more experimental data must be accessible.

No description available.

Use of biofuels, especially in automotive applications, is a growing trend due to their potential to lower greenhouse gas emissions from combustion. Ketones are a class of biofuel candidates which are produced from cellulose. However, ketones received rather scarce attention from the combustion community compared to other classes such as, alcohols, esters, and ethers. There is little knowledge on their combustion performance and pollutant generation. Hence their combustion chemistry needs to be investigated in detail. Diisopropyl ketone (DIPK) is a promising biofuel candidate, which is produced using endophytic fungal conversion. A detailed understanding of the combustion kinetics of the oxidation of DIPK in advanced engines such as, the homogeneous charge compression ignition (HCCI) engine is warranted. This dissertation concentrates on the combustion kinetics of DIPK over a wide range of temperature and pressure with a focus on HCCI engine application. An existing DIPK kinetic mechanism has been reviewed and a single zone HCCI engine model has been modeled and validated against recent experimental data from Sandia National Lab. Therefore different HCCI modeling assumptions were tested and the DIPK reaction mechanism was modified with missing reactions and the required thermochemical data. As a result, the HCCI pressure trace, heat release rate and reactivity have been improved. In order to improve the ignition delay time simulation results, the low temperature oxidation of DIPK was studied as the fuel chemistry effects on the autoignition behavior becomes important in low temperature. Therefore DIPK low temperature oxidation experimental data was obtained from the synchrotron photoionization experiments conducted at the Advanced Light Source (ALS) so that the primary products as well as the dominant oxidation pathways are identified. Furthermore, the aldehydes oxidation, as a result of partial or incomplete combustion and as the primary stable intermediate products in oxidation and pyrolysis of biofuel were studied at low temperature in ALS. A high temperature reaction mechanism was created using the reaction class approach. The reaction mechanism for DIPK was improved using the experimental data along with quantum chemical calculation of activation energies and barriers as well as vibrational modes for the important reactions identified in ALS experiment. The rate constants for important reactions were calculated based on modified Arrhenius equation. DIPK oxidation and pyrolysis were studied at high temperature and pressure using UCF shock tube. The ignition delay times as well as the product (methane) time histories were investigated and used as validation targets for the new model.

Industrial gas turbines constitute an integral part of today’s electricalpower production infrastructure. Reacting gas flows in these machines arevery interesting and complex in nature since they exhibit highly turbulentbehaviour which is strongly coupled to the chemical reaction dynamics.Thus developing accurate CFD models for such flows while keeping thecomputational expense reasonable is a non-trivial task. In this studyLarge-Eddy simulations of hydrogen-methane fuel mixture combustion inthe SGT800’s (Siemens Energy Gas turbine 800) burner, in atmosphericconditions are performed using the CFD code Starccm+ (versions 16.04and 16.06).

The advent of detonation-based propulsion systems represents an opportunity for more sustainable combustion processes and hypersonic travel. In regular detonations, some yet to be resolved instabilities are attributed to the propagation and collision of triple points, formed at the intersection of a Mach stem, an incident shock and a transverse wave. Over time, the tracks observed by these points form a structure made of diamond-shaped cells. Ultimately, The ability to sustain these instabilities plays a key role in the propagation of detonations. The present work unveils the dynamics of gaseous detonations at a sub-cellular level. The experiments are conducted with hydrogen fuel which is of great potential for detonation engine applications. The hydrogen-oxygen mixtures are held at stoichiometry and the nitrogen dilution in oxygen is varied from 30% to 70%. This allows to observe the effects of activation energy through the dilution on the sub-cellular wave dynamics. Measurements of cell sizes and wave velocity are reported through shadowgraph imaging. A new methodology is developed for the simultaneous resolution of the velocity field and cellular structure. The statistical analysis is made possible due to the design of a fully automated detonation facility. The experiments are conducted in a thin channel to minimize gradients in the third direction and confine the detonation cells to a plane. The results in cell sizes are in good agreement with the literature and expand the conditions reported thus far. Local observations of the velocity within the cells are used to explain the regularity of the overall wave speed, found to increase at lower dilution. Lastly, high fidelity simulations are conducted to model the cellular structure in hydrogen-air oblique detonation waves. Similarly to the experiments, the velocity field is extracted along the detonation cells and reveals the effects of wave curvature on triple point dynamics.

No description available.

Two new models to calculate the species instantaneous and filtered reaction rates for multi-step, multi-species chemical kinetics mechanisms are developed based on the artificial neural networks (ANN) approach. The proposed methodologies depend on training the ANNs off-line on a thermo-chemical database representative of the actual composition and turbulence level of interest. The thermo-chemical database is constructed by stand-alone linear eddy mixing (LEM) model simulations under both premixed and non-premixed conditions, where the unsteady interaction of turbulence with chemical kinetics is included as a part of the training database. In this approach, the information regarding the actual geometry of interest is not needed within the LEM computations. The developed models are validated extensively on the large eddy simulations (LES) of (i) premixed laminar-flame-vortex-turbulence interaction, (ii) temporally mixing non-premixed flame with extinction-reignition characteristics, and (iii) stagnation point reverse flow combustor, which utilizes exhaust gas re-circulation technique. Results in general are satisfactory, and it is shown that the ANN provides considerable amount of memory saving and speed-up with reasonable and reliable accuracy. The speed-up is strongly affected by the stiffness of the reduced mechanism used for the computations, whereas the memory saving is considerable regardless.