Modeling of nitrogen oxides formation and destruction in combustion systems

The numerical study of engine combustion requires the coupling of advanced computational fluid dynamics and accurate chemical kinetic models. This task becomes extremely challenging for real fuels. Gasoline is a mixture of hundreds of different hydrocarbons. Detailed modeling of its chemistry requires huge numbers of species and reactions and exceeds present numerical capabilities. Consequently, simpler surrogate mixtures are adopted to approximate the behavior of the real fuels. Large kinetic models for surrogates are developed to characterize their chemistry, but these models still contain thousands of species and reactions and can usually only be used for simulating simple homogeneous systems. For multidimensional engine applications, they must be reduced. In this work, we propose a methodology for the formulation of a gasoline surrogates based on the intrinsic qualities of the fuel chemical behavior. Using the proposed procedure, a candidate surrogate containing four components has been identified to ...

An Approach for Formulating Surrogates for Gasoline with Application toward a Reduced Surrogate Mechanism for CFD Engine Modeling

An existing skeletal mechanism for laminar premixed methane/air flames has been used as a starting point for further automatic reduction by quasi-steady-state approximation (QSSA) for species with short chemical lifetimes and/or minor influence on the chemical system Individual species are ranked with respect to static and dynamic characteristics according to a level of importance (LOI) measure obtained from their chemical lifetimes, diffusion velocities and flame-zone residence times in combination with a species sensitivity measure The maximum element mass fraction and the maximum enthalpy occupied by a certain molecular species are constrained in order to limit the mass and energy deficiency caused by QSSA Maximum values of lifetime and LOI are accumulated over the entire flame length for a range of fuel/air equivalence ratios  Species with low LOI are selected for QSSA, and their concentrations are calculated iteratively by solving the coupled algebraic system Kinetic models with a varying degree of reduction are then automatically generated and implemented as FORTRAN source code by setting different lower LOI and element mass fraction limits It is found that the lifetime and LOI measure differ due to the inclusion of sensitivity counteracting the rise in lifetime at low temperatures The species ranking by the LOI disfavors reasonably stable species, which are removed from the system The laminar burning velocities as predicted by the most strongly reduced mechanism with five global reaction steps show very good agreement with detailed calculations The profiles of steady-state species also agree well if, the corresponding species lifetime is short

Automatic reduction procedure for chemical mechanisms applied to premixed methane/air flames

Several alternative techniques have been proposed in the literature in order to avoid the CPU-intensive numerical integration of the thermochemical equations in the simulation of combustion processes. The present paper introduces a new approach, which is based on two artificial neural-network (ANN) paradigms, namely the self-organizing map (SOM) and the multilayer perceptron (MLP). The SOM is first employed for the automatic partitioning of the thermochemical space into subdomains. Then, a specialized MLP is trained in order to fit the thermochemical points belonging to a given subdomain. The presented strategy is tested on a partially stirred reactor (PaSR) with a reduced methane-air mechanism, and encouraging results are reported. The relatively modest CPU-time and memory requirements of the method make the SOM-MLP approach a promising technique for the inclusion of large chemical mechanisms in the context of complex applications, such as the multidimensional simulation of combustion.

A self-organizing-map approach to chemistry representation in combustion applications

The tremendous increase in energy demand due to increased population and rapid economics results in an increased level of atmospheric pollutants and global warming. The global shift to the use of renewable clean energies still has some restrictions in terms of the availability of the advanced reliable technologies and the cost of application compared to conventional fossil fuels. Until we can have this full conversion to renewables, the development of novel techniques for clean combustion of fossil fuels is appreciated. Forced by the simultaneous increased pressure of strict emissions regulations and the target of limiting the global warming to 2 °C, gas turbine manufacturers developed novel combustion techniques for clean power production in gas turbines as per the present review study. These novel techniques depend either on modification in the existing combustion system or developing novel burners for clean power production. In this review, different clean combustion techniques are presented including ...

Review of Novel Combustion Techniques for Clean Power Production in Gas Turbines

This study has identified useful reduced kinetic schemes that can be used in comprehensive multidimensional gas-turbine combustor models. Reduced mechanisms lessen computational cost and possess the capability to accurately predict the overall flame structure, including gas temperatures and key intermediate species such as CH{sub 4}, CO, and NO{sub x}. In this study, four new global mechanisms with five, six, seven, and nine steps based on the full GRI 2.11 mechanism, were developed and evaluated for their potential to model natural gas chemistry (including NO{sub x} chemistry) in gas turbine combustors. These new reduced mechanisms were optimized to model the high pressure and fuel-lean conditions found in gas turbines operating in the lean premixed mode. Based on perfectly stirred reactor (PSR) and premixed code calculations, the five-step reduced mechanism was identified as a promising model that can be used in a multidimensional gas-turbine code for modeling lean-premixed, high-pressure turbulent combustion of natural gas. Predictions of temperature, CO, CH{sub 4}, and NO from the five- to nine-step reduced mechanisms agree within 5% of the predictions from the full kinetic model for 1 < pressure (atm) < 30, and 0.6 < {phi} < 1.0. If computational costs due to additional global steps aremore » not severe, the newly developed nine step global mechanism, which is a little more accurate and provided the least convergence problems, can be used. Future experimental research in gas turbine combustion will provide more accurate data, which will allow the formulation of better full and reduced mechanisms. Also, improvement in computational approaches and capabilities will allow the use of reduced mechanisms with larger global steps, perhaps full mechanisms.« less

Evaluation of CH4/NOx Reduced Mechanisms Used for Modeling Lean Premixed Turbulent Combustion of Natural Gas

This paper describes recent development of iso-octane skeletal and reduced mechanisms for speeding up numerical simulations of homogeneous charge compression ignition (HCCI) engines. A novel targeted search algorithm is developed to systematically screen species for quasisteady state (QSS) assumption in order to reduce the mechanism size while maintaining accuracy. This new approach is especially found useful when the chemical kinetics involve complex ignition pathways. Using the iso-octane mechanism developed by LLNL, a skeletal mechanism with 215 species (Skeletal-215) and a reduced mechanism with 63 non-QSS species (Reduced-63) were constructed. Evaluations of the performances of the Skeletal-215 and the Reduced-63 were extensively conducted for the operation regimes in HCCI engine applications. Both mechanisms are found satisfactory in predicting start of combustion and minor emission species.

J. Y. Chen

Papers

Evaluation of CH4/NOx Reduced Mechanisms Used for Modeling Lean Premixed Turbulent Combustion of Natural Gas

Development of a Highly Reduced Mechanism for Iso-Octane HCCI Combustion With Targeted Search Algorithm